NVIDIA's own Dr. Ian Buck, alongside others in his field, has come before a United States Congressional Committee to ask the U.S. government to not only accept artificial intelligence but begin integrating it into everyday society and government operations. Buck, who is the vice president and general manager of NVIDIA's business relationship and operations with Tesla, called for the government to increase its funding and emphasis on AI research. According to Buck, governments around the world have been stepping up funding and manpower in AI research and integration, while the United States has largely been leaving the development of such technology to the Silicon Valley. He asked for agencies like DARPA, the NIH, and the NSF to get involved in researching and integrating AI technology.
Buck went into detail about which areas of government operation could benefit from the inclusion of AI technology, zeroing in on the medical field. He spoke to the Subcommittee On Information Technology alongside panel members including the Allen Institute for Artificial Intelligence's Dr. Oren Etzioni, Georgia Institute of Technology's Dr. Charles Isbell, and Intel's Dr. Amir Khosrowshahi. The panel echoed Buck's sentiment, and also called for the U.S. government to invest more in the factors that go into AI development, including emphasizing the inclusion of STEM curriculum in public school students' normal studies in order to foster the continued growth and advancement of the tech circle.
NVIDIA is one of the world's pioneers in ongoing AI research, development, and implementation. While the company may not be focused on entirely new applications of AI or churning out interesting concepts in the vein of Google's DeepMind, NVIDIA has developed widely used AI chipsets and base programs that see consumer-facing use in a number of fields. The world of automobiles, including assist systems, full autonomy, and AI-based infotainment and analytics are all part of NVIDIA's portfolio. The company's long history of creating GPUs for computer gaming and 3D creation has allowed it to expand its operations into specialized chips for AI workloads that are similar in a number of ways to its GPU chips and use many of the same basic computing principles and architectures.